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On-line adaptive control of robot manipulators using dynamic fuzzy neural networks

Gao, Yang and Er, M.J. and Leithead, W.E. and Leith, D.J. (2001) On-line adaptive control of robot manipulators using dynamic fuzzy neural networks. In: American Control Conference, 2001-06-25 - 2001-06-27, Arlington, VA, USA.

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Abstract

This paper presents a robust Adaptive Fuzzy Neural Controller (AFNC) suitable for motion control of a multilink robot manipulator. The proposed controller has the following salient features: (1) dynamic fuzzy neural networks structure, i.e. fuzzy control rules can be generated or deleted automatically, (2) adaptive learning, (3) online learning of the robot dynamics, (4) fast learning speed, and (5) fast convergence of tracking error. Global stability of the system is established using Lyapunov approach. Computer simulation studies of a two-link robot manipulator demonstrate that excellent tracking performance can be achieved under external disturbances

Item type: Conference or Workshop Item (Paper)
ID code: 37525
Keywords: on-line , adaptive control, robot manipulators, dynamic , fuzzy neural networks, Electrical engineering. Electronics Nuclear engineering
Subjects: Technology > Electrical engineering. Electronics Nuclear engineering
Department: Faculty of Engineering > Electronic and Electrical Engineering
Related URLs:
    Depositing user: Pure Administrator
    Date Deposited: 09 Feb 2012 14:40
    Last modified: 06 Sep 2014 17:48
    URI: http://strathprints.strath.ac.uk/id/eprint/37525

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